814 citations · 2.2k across the 32 of their papers we have counts for
35 papers
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah +117
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. I…
Unsupervised bias discovery in medical image segmentation
Nicolás Gaggion, Rodrigo Echeveste, Lucas Mansilla +2
It has recently been shown that deep learning models for anatomical segmentation in medical images can exhibit biases against certain sub-populations defined in terms of protected…
CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images
Nicolás Gaggion, Candelaria Mosquera, Lucas Mansilla +4
The development of successful artificial intelligence models for chest X-ray analysis relies on large, diverse datasets with high-quality annotations. While several databases of ch…
Towards unraveling calibration biases in medical image analysis
María Agustina Ricci Lara, Candelaria Mosquera, Enzo Ferrante +1
In recent years the development of artificial intelligence (AI) systems for automated medical image analysis has gained enormous momentum. At the same time, a large body of work ha…
Are demographically invariant models and representations in medical imaging fair?
Eike Petersen, Enzo Ferrante, Melanie Ganz +1
Medical imaging models have been shown to encode information about patient demographics such as age, race, and sex in their latent representation, raising concerns about their pote…
Unsupervised ensemble-based phenotyping helps enhance the discoverability of genes related to heart morphology
Rodrigo Bonazzola, Enzo Ferrante, Nishant Ravikumar +5
Recent genome-wide association studies (GWAS) have been successful in identifying associations between genetic variants and simple cardiac parameters derived from cardiac magnetic…